scholarly journals The genetic architecture of medication-use

2020 ◽  
Author(s):  
Palle Duun Rohde ◽  
Peter Sørensen ◽  
Mette Nyegaard
Keyword(s):  
Medical Treatment ◽  
Allele Frequency ◽  
Minor Allele Frequency ◽  
Genetic Variants ◽  
Genetic Architecture ◽  
Association Studies ◽  
Medication Use ◽  
Minor Allele ◽  
Genome Wide Association Studies ◽  
Common Genetic Variants

AbstractGenomics has been forecasted to revolutionise human health by improving medical treatment through a better understanding of the molecular mechanisms of human diseases. Despite great successes of the last decade’s genome-wide association studies (GWAS), the results have to a limited extent been translated to genomic medicine. We propose, that one route to get closer to improved medical treatment is by understanding the genetics of medication-use. Here we obtained entire medication profiles from 335,744 individuals from the UK Biobank and performed a GWAS to identify which common genetic variants are major drivers of medication-use. We analysed 9 million imputed genetic variants, estimated SNP heritability, partitioned the genomic variance across functional categories, and constructed genetic scores for medication-use. In total, 59 independent loci were identified for medication-use and approximately 18% of the total variation was attributable to common genetic (minor allele frequency >0.01) variants. The largest fraction of variance was captured by variants with low to medium minor allele frequency. In particular coding and conserved regions, as well as transcription start sites, displayed significantly enrichment of heritability. The average correlation between medication-use and predicted genetic scores was 0.14. These results demonstrate that medication-use per se is a highly polygenic complex trait and that individuals with higher genetic liability are on average more diseased and have a higher risk for adverse drug reactions. These results provide an insight into the genetic architecture of medication use and pave the way for developments of multicomponent genetic risk models that includes the genetically informed medication-use.

scholarly journals Comparison of the Performance of Two Commercial Genome-Wide Association Study Genotyping Platforms in Han Chinese Samples

2013 ◽  
Vol 3 (1) ◽  
pp. 23-29 ◽  
Author(s):  
Lei Jiang ◽  
Dana Willner ◽  
Patrick Danoy ◽  
Huji Xu ◽  
Matthew A Brown
Keyword(s):  
Allele Frequency ◽  
Minor Allele Frequency ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Han Chinese ◽  
Minor Allele ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genome Wide

Abstract Most genome-wide association studies to date have been performed in populations of European descent, but there is increasing interest in expanding these studies to other populations. The performance of genotyping chips in Asian populations is not well established. Therefore, we sought to test the performance of widely used fixed-marker, genome-wide association studies chips in the Han Chinese population. Non-HapMap Chinese samples (n = 396) were genotyped using the Illumina OmniExpress and Affymetrix 6.0 platforms, whereas a subset also were genotyped using the Immunochip. Genotyped markers from the Affymetrix 6.0 and Illumina OmniExpress were used for full genome imputation based on the HapMap 2 JPT+CHB (Japanese from Tokyo, Japan and Chinese from Beijing, China) reference panel. The concordance between markers genotypes for the three platforms was very high whether directly genotyped or genotyped and imputed single nucleotide polymorphisms (SNPs; >99.8% for directly genotyped and >99.5% for genotyped and imputed SNPs, respectively) were compared. The OmniExpress chip data enabled more SNPs to be imputed, particularly SNPs with minor allele frequency >5%. The OmniExpress chip achieved better coverage of HapMap SNPs than the Affymetrix 6.0 chip (73.6% vs. 65.9%, respectively, for minor allele frequency >5%). The Affymetrix 6.0 and Illumina OmniExpress chip have similar genotyping accuracy and provide similar accuracy of imputed SNPs. The OmniExpress chip however provides better coverage of Asian HapMap SNPs, although its coverage of HapMap SNPs is moderate.

scholarly journals Estimation of linkage disequilibrium levels and allele frequency distribution in crossbred Vrindavani cattle using 50K SNP data

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0259572
Author(s):  
Akansha Singh ◽  
Amit Kumar ◽  
Arnav Mehrotra ◽  
Karthikeyan A. ◽  
Ashwni Kumar Pandey ◽  
...  
Keyword(s):  
Linkage Disequilibrium ◽  
Allele Frequency ◽  
Minor Allele Frequency ◽  
Association Studies ◽  
Minor Allele ◽  
Pairwise Distance ◽  
Allele Frequency Distribution ◽  
Genome Wide Association Studies ◽  
Effective Population ◽  
Autosomal Snps

The objective of this study was to calculate the extent and decay of linkage disequilibrium (LD) in 96 crossbred Vrindavani cattle genotyped with Bovine SNP50K Bead Chip. After filtering, 43,821 SNPs were retained for final analysis, across 2500.3 Mb of autosome. A significant percentage of SNPs was having minor allele frequency of less than 0.20. The extent of LD between autosomal SNPs up to 10 Mb apart across the genome was measured using r2 statistic. The mean r2 value was 0.43, if pairwise distance of marker was less than10 kb and it decreased further to 0.21 for 25–50 kb markers distance. Further, the effect of minor allele frequency and sample size on LD estimate was investigated. The LD value decreased with the increase in inter-marker distance, and increased with the increase of minor allelic frequency. The estimated inbreeding coefficient and effective population size were 0.04, and 46 for present generation, which indicated small and unstable population of Vrindavani cattle. These findings suggested that a denser or breed specific SNP panel would be required to cover all genome of Vrindavani cattle for genome wide association studies (GWAS).

scholarly journals Shared genetic background between children and adults with attention deficit/hyperactivity disorder

2019 ◽  
Author(s):  
Paula Rovira ◽  
Ditte Demontis ◽  
Cristina Sánchez-Mora ◽  
Tetyana Zayats ◽  
Marieke Klein ◽  
...  
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Attention Deficit ◽  
Genetic Variants ◽  
Genetic Background ◽  
Genetic Architecture ◽  
Neurodevelopmental Disorder ◽  
Genome Wide Association Studies ◽  
Hyperactivity Disorder ◽  
Common Genetic Variants ◽  
Shared Genetic

AbstractAttention deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder characterized by age-inappropriate symptoms of inattention, impulsivity and hyperactivity that persist into adulthood in the majority of the diagnosed children. Despite several risk factors during childhood predicting the persistence of ADHD symptoms into adulthood, the genetic architecture underlying the trajectory of ADHD over time is still unclear. We set out to study the contribution of common genetic variants to the risk for ADHD across the lifespan by conducting meta-analyses of genome-wide association studies on persistent ADHD in adults and ADHD in childhood separately and comparing the genetic background between them in a total sample of 17,149 cases and 32,411 controls. Our results show nine new independent loci and support a shared contribution of common genetic variants to ADHD in children and adults. No subgroup heterogeneity was observed among children, while this group consists of future remitting and persistent individuals. We report similar patterns of genetic correlation of ADHD with other ADHD-related datasets and different traits and disorders among adults, children and when combining both groups. These findings confirm that persistent ADHD in adults is a neurodevelopmental disorder and extend the existing hypothesis of a shared genetic architecture underlying ADHD and different traits to a lifespan perspective.

scholarly journals Association of common genetic variants with brain microbleeds

Neurology ◽  
2020 ◽  
Vol 95 (24) ◽  
pp. e3331-e3343 ◽  
Author(s):  
Maria J. Knol ◽  
Dongwei Lu ◽  
Matthew Traylor ◽  
Hieab H.H. Adams ◽  
José Rafael J. Romero ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Small Vessel Disease ◽  
Association Studies ◽  
Cerebral Small Vessel Disease ◽  
Small Vessel ◽  
White Matter Hyperintensity ◽  
Genome Wide Association Studies ◽  
Vessel Disease ◽  
Genome Wide ◽  
Common Genetic Variants

ObjectiveTo identify common genetic variants associated with the presence of brain microbleeds (BMBs).MethodsWe performed genome-wide association studies in 11 population-based cohort studies and 3 case–control or case-only stroke cohorts. Genotypes were imputed to the Haplotype Reference Consortium or 1000 Genomes reference panel. BMBs were rated on susceptibility-weighted or T2*-weighted gradient echo MRI sequences, and further classified as lobar or mixed (including strictly deep and infratentorial, possibly with lobar BMB). In a subset, we assessed the effects of APOE ε2 and ε4 alleles on BMB counts. We also related previously identified cerebral small vessel disease variants to BMBs.ResultsBMBs were detected in 3,556 of the 25,862 participants, of which 2,179 were strictly lobar and 1,293 mixed. One locus in the APOE region reached genome-wide significance for its association with BMB (lead single nucleotide polymorphism rs769449; odds ratio [OR]any BMB [95% confidence interval (CI)] 1.33 [1.21–1.45]; p = 2.5 × 10−10). APOE ε4 alleles were associated with strictly lobar (OR [95% CI] 1.34 [1.19–1.50]; p = 1.0 × 10−6) but not with mixed BMB counts (OR [95% CI] 1.04 [0.86–1.25]; p = 0.68). APOE ε2 alleles did not show associations with BMB counts. Variants previously related to deep intracerebral hemorrhage and lacunar stroke, and a risk score of cerebral white matter hyperintensity variants, were associated with BMB.ConclusionsGenetic variants in the APOE region are associated with the presence of BMB, most likely due to the APOE ε4 allele count related to a higher number of strictly lobar BMBs. Genetic predisposition to small vessel disease confers risk of BMB, indicating genetic overlap with other cerebral small vessel disease markers.

scholarly journals Contributions of common genetic variants to risk of schizophrenia among individuals of African and Latino ancestry

2019 ◽  
Vol 25 (10) ◽  
pp. 2455-2467 ◽  
Author(s):  
Tim B. Bigdeli ◽  
◽  
Giulio Genovese ◽  
Penelope Georgakopoulos ◽  
Jacquelyn L. Meyers ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Association Studies ◽  
Large Fraction ◽  
African Ancestry ◽  
Common Variant ◽  
Human Populations ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Common Genetic Variants

Abstract Schizophrenia is a common, chronic and debilitating neuropsychiatric syndrome affecting tens of millions of individuals worldwide. While rare genetic variants play a role in the etiology of schizophrenia, most of the currently explained liability is within common variation, suggesting that variation predating the human diaspora out of Africa harbors a large fraction of the common variant attributable heritability. However, common variant association studies in schizophrenia have concentrated mainly on cohorts of European descent. We describe genome-wide association studies of 6152 cases and 3918 controls of admixed African ancestry, and of 1234 cases and 3090 controls of Latino ancestry, representing the largest such study in these populations to date. Combining results from the samples with African ancestry with summary statistics from the Psychiatric Genomics Consortium (PGC) study of schizophrenia yielded seven newly genome-wide significant loci, and we identified an additional eight loci by incorporating the results from samples with Latino ancestry. Leveraging population differences in patterns of linkage disequilibrium, we achieve improved fine-mapping resolution at 22 previously reported and 4 newly significant loci. Polygenic risk score profiling revealed improved prediction based on trans-ancestry meta-analysis results for admixed African (Nagelkerke’s R2 = 0.032; liability R2 = 0.017; P < 10−52), Latino (Nagelkerke’s R2 = 0.089; liability R2 = 0.021; P < 10−58), and European individuals (Nagelkerke’s R2 = 0.089; liability R2 = 0.037; P < 10−113), further highlighting the advantages of incorporating data from diverse human populations.

Performance of polygenic risk scores for cancer prediction in an academic biobank.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 1528-1528
Author(s):  
Heena Desai ◽  
Anh Le ◽  
Ryan Hausler ◽  
Shefali Verma ◽  
Anurag Verma ◽  
...  
Keyword(s):  
Risk Score ◽  
Genetic Variants ◽  
Association Studies ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
European Americans ◽  
Genome Wide ◽  
Common Genetic Variants

1528 Background: The discovery of rare genetic variants associated with cancer have a tremendous impact on reducing cancer morbidity and mortality when identified; however, rare variants are found in less than 5% of cancer patients. Genome wide association studies (GWAS) have identified hundreds of common genetic variants significantly associated with a number of cancers, but the clinical utility of individual variants or a polygenic risk score (PRS) derived from multiple variants is still unclear. Methods: We tested the ability of polygenic risk score (PRS) models developed from genome-wide significant variants to differentiate cases versus controls in the Penn Medicine Biobank. Cases for 15 different cancers and cancer-free controls were identified using electronic health record billing codes for 11,524 European American and 5,994 African American individuals from the Penn Medicine Biobank. Results: The discriminatory ability of the 15 PRS models to distinguish their respective cancer cases versus controls ranged from 0.68-0.79 in European Americans and 0.74-0.93 in African Americans. Seven of the 15 cancer PRS trended towards an association with their cancer at a p<0.05 (Table), and PRS for prostate, thyroid and melanoma were significantly associated with their cancers at a bonferroni corrected p<0.003 with OR 1.3-1.6 in European Americans. Conclusions: Our data demonstrate that common variants with significant associations from GWAS studies can distinguish cancer cases versus controls for some cancers in an unselected biobank population. Given the small effects, future studies are needed to determine how best to incorporate PRS with other risk factors in the precision prediction of cancer risk. [Table: see text]

scholarly journals A global overview of pleiotropy and genetic architecture in complex traits

2018 ◽  
Author(s):  
Kyoko Watanabe ◽  
Sven Stringer ◽  
Oleksandr Frei ◽  
Maša Umićević Mirkov ◽  
Tinca J.C. Polderman ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Complex Traits ◽  
Genetic Architecture ◽  
Human Genetics ◽  
Association Studies ◽  
Regulatory Elements ◽  
Genome Wide Association Studies ◽  
Multiple Trait ◽  
Current Availability ◽  
Flanking Regions

ABSTRACTAfter a decade of genome-wide association studies (GWASs), fundamental questions in human genetics are still unanswered, such as the extent of pleiotropy across the genome, the nature of trait-associated genetic variants and the disparate genetic architecture across human traits. The current availability of hundreds of GWAS results provide the unique opportunity to gain insight into these questions. In this study, we harmonized and systematically analysed 4,155 publicly available GWASs. For a subset of well-powered GWAS on 558 unique traits, we provide an extensive overview of pleiotropy and genetic architecture. We show that trait associated loci cover more than half of the genome, and 90% of those loci are associated with multiple trait domains. We further show that potential causal genetic variants are enriched in coding and flanking regions, as well as in regulatory elements, and how trait-polygenicity is related to an estimate of the required sample size to detect 90% of causal genetic variants. Our results provide novel insights into how genetic variation contributes to trait variation. All GWAS results can be queried and visualized at the GWAS ATLAS resource (http://atlas.ctglab.nl).

scholarly journals Lipid associated polygenic enrichment in Alzheimer’s disease

2018 ◽  
Author(s):  
Iris J. Broce ◽  
Chin Hong Tan ◽  
Chun Chieh Fan ◽  
Aree Witoelar ◽  
Natalie Wen ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Genetic Variants ◽  
Plasma Lipids ◽  
Association Studies ◽  
Density Lipoprotein ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genetic Pleiotropy ◽  
Common Genetic Variants

ABSTRACTCardiovascular (CV) and lifestyle associated risk factors (RFs) are increasingly recognized as important for Alzheimer’s disease (AD) pathogenesis. Beyond the ∊4 allele of apolipoprotein E (APOE), comparatively little is known about whether CV associated genes also increase risk for AD (genetic pleiotropy). Using large genome-wide association studies (GWASs) (total n > 500,000 cases and controls) and validated tools to quantify genetic pleiotropy, we systematically identified single nucleotide polymorphisms (SNPs) jointly associated with AD and one or more CV RFs, namely body mass index (BMI), type 2 diabetes (T2D), coronary artery disease (CAD), waist hip ratio (WHR), total cholesterol (TC), low-density (LDL) and high-density lipoprotein (HDL). In fold enrichment plots, we observed robust genetic enrichment in AD as a function of plasma lipids (TC, LDL, and HDL); we found minimal AD genetic enrichment conditional on BMI, T2D, CAD, and WHR. Beyond APOE, at conjunction FDR < 0.05 we identified 57 SNPs on 19 different chromosomes that were jointly associated with AD and CV outcomes including APOA4, ABCA1, ABCG5, LIPG, and MTCH2/SPI1. We found that common genetic variants influencing AD are associated with multiple CV RFs, at times with a different directionality of effect. Expression of these AD/CV pleiotropic genes was enriched for lipid metabolism processes, over-represented within astrocytes and vascular structures, highly co-expressed, and differentially altered within AD brains. Beyond APOE, we show that the polygenic component of AD is enriched for lipid associated RFs. Rather than a single causal link between genetic loci, RF and the outcome, we found that common genetic variants influencing AD are associated with multiple CV RFs. Our collective findings suggest that a network of genes involved in lipid biology also influence Alzheimer’s risk.

scholarly journals An integrated platform to systematically identify causal variants and genes for polygenic human traits

2019 ◽  
Author(s):  
Damien J. Downes ◽  
Ron Schwessinger ◽  
Stephanie J. Hill ◽  
Lea Nussbaum ◽  
Caroline Scott ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Association Studies ◽  
Significant Proportion ◽  
Genome Wide Association Studies ◽  
Effector Genes ◽  
Genome Wide ◽  
Common Genetic Variants ◽  
Integrated Platform ◽  
Causal Variants

ABSTRACTGenome-wide association studies (GWAS) have identified over 150,000 links between common genetic variants and human traits or complex diseases. Over 80% of these associations map to polymorphisms in non-coding DNA. Therefore, the challenge is to identify disease-causing variants, the genes they affect, and the cells in which these effects occur. We have developed a platform using ATAC-seq, DNaseI footprints, NG Capture-C and machine learning to address this challenge. Applying this approach to red blood cell traits identifies a significant proportion of known causative variants and their effector genes, which we show can be validated by direct in vivo modelling.

scholarly journals Flaw or discovery? Calculating exact p-values for genome-wide association studies in inbred populations

2015 ◽  
Author(s):  
Xia Shen
Keyword(s):  
Allele Frequency ◽  
Frequency Distribution ◽  
Minor Allele Frequency ◽  
Association Studies ◽  
Genome Wide Association ◽  
Allele Frequency Distribution ◽  
Genome Wide Association Studies ◽  
P Values ◽  
Genome Wide ◽  
Inbred Populations

Motivation: Genome-wide association studies have been conducted in inbred populations where the sample size is small. The ordinary association p-values and multiple testing correction therefore become questionable, as the detected genetic effect may or may not be due to chance, depending on the minor allele frequency distribution across the genome. Instead of permutation testing, marker-specific false positive rate can be analytically calculated in inbred populations without heterozygotes. Results: Solutions of exact p-values for genome-wide association studies in inbred populations were derived and implemented. An example is presented to illustrate that the marker-specific experiment-wise p-value varies as the genome-wide minor allele frequency distribution changes. A simulation using real Arabidopsis thaliana genome indicates that the use of exact p-values improves detection power and reduces inflation due to population structure. An analysis of a defense-related case-control phenotype using the exact p-values revealed the causal locus, where markers with higher MAFs had smaller p-values than the top variants with lower MAFs in ordinary genome-wide association analysis. Availability and Implementation: Project URL: https://r-forge.r-project.org/projects/statomics/. The R package p.exact: https://r-forge.r-project.org/R/?group_id=2030.

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